# 1683 search results for "regression"

## Multi-stage sampling together with hierarchical/ mixed effects models: which packages?

November 5, 2012
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Dear R experts, I sent this question to the r-help list but didn’t get much response, probably because it is more of a stats question. But as this blog is syndicated on r-bloggers I thought I would try it again here on this blog. If I am barking up the wrong tree, feel free to

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## Unstable parallel simulation, or after finishing testing, test some more

November 2, 2012
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Lately I have been working on a trading system based on Support Vector Machine (SVM) regression (and yes, if you wonder, there are a few posts planned to share the results). In this post however I want to share an interesting problem I had to deal with. Few days ago, I started running simulations using

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## Why pictures are so important when modeling data?

October 31, 2012
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$R^2$

(bis repetita) Consider the following regression summary,Call: lm(formula = y1 ~ x1)   Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.0001 1.1247 2.667 0.02573 * x1 0.5001 0.1179 4.241 0.00217 **...

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## Hierarchical linear models and lmer

October 31, 2012
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Hierarchical linear models and lmer Article by Ben Ogorek Graphics by Bob Forrest Background My last article featured linear models with random slopes. For estimation and prediction, we used the lmer function from the lme4 package. Today we'll consider another level in the hierarchy, one...

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## Visiting FHCRC, JHSPH and Meeting Xi’an

October 29, 2012
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I have been traveling during the last two weeks. I visited Fred Hutchinson Cancer Research Center on Oct 16 and the Department of Biostatistics at Johns Hopkins at the invitation of Simply Statistics on Oct 23. Today Christian Robert was visiting our department at Iowa State, and I also talked to him. It is really cool...

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## the large half now

October 28, 2012
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The little half puzzle proposed a “dumb’ solution in that players play a minimax strategy. There are 34 starting values less than 100 guaranteeing a sure win to dumb players. If instead the players maximise their choice at each step, the R code looks like this: and there are now 66 (=100-34, indeed!) starting values

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## R function: generate a panel data.table or data.frame to fill with data

October 25, 2012
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I have started to work with R and STATA together. I like running regressions in STATA, but I do graphs and setting up the dataset in R. R clearly has a strong comparative advantage here compared to STATA. I was writing a function that will give me a (balanced) panel-structure in R. It then simply

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## The basics of Value at Risk and Expected Shortfall

October 23, 2012
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Value at Risk and Expected Shortfall are common risk measures.  Here is a quick explanation. Ingredients The first two ingredients are each a number: The time horizon — how many days do we look ahead? The probability level — how far in the tail are we looking? Ingredient number 3 is a prediction distribution of … Continue reading...

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## Predict User’s Return Visit within a day part-3

October 22, 2012
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Welcome to the last part of the series on predicting user’s revisit to the website. In the  first part of series, I generated the logistic regression model for prediction problem whether a user will come back on  website in next 24 hours. In the second part, I discussed about model improvement and seen the model accuracy.

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## Predict User’s Return Visit within a day part-2

October 22, 2012
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Welcome to the second part of the series on predicting user’s revisit to the website. In my earlier blog Logistic Regression with R, I discussed what is logistic regression. In the first part of the series, we applied logistic regression to available data set. The problem statement there was whether a user will return in

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